UNDERSTANDING LOCAL PERFORMANCE ART AUDIENCE: SEGMENTATION ... · PDF fileUNDERSTANDING LOCAL PERFORMANCE ART AUDIENCE: SEGMENTATION STUDY ... One contributing factor to this low performance

ICEBESS 2016 Proceeding

International Conference on Ethics of Business, Economics, and Social Science || 299

UNDERSTANDING LOCAL PERFORMANCE ART AUDIENCE:

SEGMENTATION STUDY

Benita Vania1, Ira Fachira1

1School of Business and Management, Institut Teknologi Bandung, Indonesia

Email: [email protected]

Abstract

In recent years, there is a global trend in maximizing the potential of creative industry,as it fuels the economy as a whole. The same path is taken by Indonesian government,which has a vision to turn creative industry into the nation�s economic powerhouse in 2025. In order to achieve this, all sectors of creative industry should be developed.Performing art is one sector in creative industry that is in the bottom two in terms ofeconomic contribution. One contributing factor to this low performance is the lack ofunderstanding the target audience, which is depicted by the lack of research in thisarea. This 6-month study analyses the demographic and physiographic profiles of theaudiences. This research uses quantitative method for the data collection and clusteranalysis for the data analysis. The result indicates that there are six groups ofaudiences, which have different profiles, motivations, and preferences in watching artperformances. This unprecedented study aims to lay as a fundamental knowledge inIndonesian performing art marketing, in order to suit the needs and wants of theaudiences better. It is hoped that this research could help performing art organizationsin Indonesia and develop the sector as a whole.

Keywords: consumer behavior, marketing research, performing art, segmentation.

INTRODUCTION

Kotler & Scheff (1997) argues that effective marketing strategy relies on deep understanding

of the motives, preferences, and behaviors of current and potential customers. As people are

different from one another, one marketing strategy may be effective to a certain types of

people and not another. Thus, it is best to divide customers into groups or segments, and use

it as a basis on which a marketing strategy is formed. The following research explores the

characteristics of local performance art audience in Indonesia in order to provide deeper

understanding for art marketers.

According to Indonesia Kreatif (2014a), performing art refers to activities that

include content development, show production, costume design, stage design, and lighting

design. This paper concerns mainly on local performance art, which is art shows that are

held by Indonesian in Indonesia. Performing art is one of sixteen subsectors of creative

industry, which has been actively promoted by Indonesian government since 2009. That

being said, performance art only contributed 0.4% to creative industry share in GDP in 2013

(Indonesia Kreatif, 2014a), which is relatively low compared to other subsectors, for instance

culinary, fashion, and crafts, which contributed 32.5%, 28.3%, and 14.4%, respectively. It is

also relatively low compared to that of other countries, such as in the United Kingdom,

United States, European Union, and Japan, as depicted in table 1.

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300 || International Conference on Ethics of Business, Economics, and Social Science

The low contribution of performing arts is ironic because Indonesia has a lot of

potential in this industry, due to its abundance of both traditional and contemporary arts. It

could be inferred that performing art in Indonesia is an untapped potential that would signify

the creative industry in Indonesia and contribute to the economy. The low contribution

compared to aforementioned countries thus indicates a room for growth for this industry.

Table 1: Country comparison of performing art contribution to creative industry revenue,adapted from: The Stage (2015), EY (2014), National Assembly of State Arts Agencies

(2015), Kakiuchi & Takeuchi (2014), Indonesia Kreatif (2014a)

Region Year Contribution of performing artto creative industry

United Kingdom 2015 7.02%European Union 2014 5.95%

United States 2012 1.73%Japan 2011 1.68%

Indonesia 2013 0.4%

From business perspective, one way for developing this industry is by utilizing its

marketing effort, as marketing plays an important role to facilitate the communication and

influence behavior, by understanding the audience and responding to their needs. According

to Indonesia Kreatif (2014b), the competitiveness of marketing in performance art scored

only 2.8 out of 10, even compared with the already-low score (4.5 out of 10) of the

competitiveness of creative industry marketing in Indonesia (figure 1). This indicates that

marketing effort in performing art industry in Indonesia is still low, and therefore an

understanding of the market is needed. So far, there is a lack of research of the audiences of

performing art in Indonesia. Swastika (2015 p. 1) wrote that |^iqelrde qeb ^rafbk`b mi^vp

an important role in the development of performance, it has generally received little

attention in discussion of the history of Indonesian performing arts, apart from journalistic

accounts, which tend to represent without research or discussion with them the opinions of

^rafbk`b jbj_bop `lk`bokfkd qeb mbocloj^k`b-}

That being said, Minarti, Tajudin, & Gesuri (2015), argues that there are two groups

of performing art audience, which are expert and amateur audiences. Expert audiences are a

group of people who are actively involved with creating performances themselves; thus, this

people watch performances of certain aesthetic quality. On the other hand, amateur

audiences are those who watch performances in order to be part of a cultural movement in

the community, to escape their daily routine and to join in expressing a critical view of actual

political and social phenomena. Aside from this basic information regarding the profile of

art performance audiences in Indonesia, there is no further research found covering this

topic. This indicates that there is a lack of understanding in Indonesian art performance

market.


International Conference on Ethics of Business, Economics, and Social Science |||| 301

Figure 1: Competitiveness index of performing art and overall creative industry, adaptedfrom Indonesia Kreatif (2014b)

The study location is major cities in Indonesia, such as Jakarta, Bandung, and

Yogyakarta. These cities are chosen as representatives of six regions that actively hold art

performances, namely special capital region of Jakarta, Central Java, West Java, East Java,

Bali, and special region of Yogyakarta (Minarti et al. 2015).

The general aim of this study is to profile performance art audiences according to

demographic, geographic, and psychographic characteristics. Therefore, this study will

assess the differences of local performance art audiences in Indonesia, create segments based

on such differences, and analyze the possible implication for art marketers. The benefit of

this study is to serve as a basis of performance art marketing in Indonesia, as marketing starts

with understanding the customers (Adams, 2015). By understanding the audience profile of

the customers, art marketers could target a certain market and create a strategy that is specific

for the target market.

LITERATURE REVIEW

A review of the literature suggests that developing a market segmentation allows the

organization to form a marketing mix that is relevant to the groups, according to the variables

they have in common (Armstrong & Kotler, 2005). In general, there are four bases on which

customer segments are built upon, which are demographic, geographic, behavioral, and

psychographic (Goyat, 2011).

Demographic segmentation divides customers into groups based on their population

attributes, for instance, age, gender, income, education, and occupation. Geographic

segmentation, on the other hand, segments customers based on geographical areas, such as

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countries- cities- and regions/ Gurthermore- behavioral segmentation is based on customers�

attitude towards a product or service. This includes occasions in which they seek the product,

usage rate, brand loyalty, and benefits sought (Goyat, 2011). Lastly, psychographic

segmentation groups customers according to their attitudes, values, lifestyles, interests, and

activities (Larsen, 2010). While traditional demographic and geographic segmentations

provide the organization with information regarding accessibility to customer segments,

psychographic segmentation provides additional information about the customers� behavior

of present and potential target markets (Gunter and Furnham, 1992, as cited in Larsen, 2010).

This study will use all four segmentations, focusing heavily on psychographic

attributes, such as motivations and influences in the decision making process. In following,

the frameworks used for the psychographic segmentation are explained.

Research Framework

The relationship between variables in this study are described in research framework below

(figure 2). This study is focused on finding the differences of people�s watching behaviour-

which are due to their differences in the influencing factors. Watching behaviour could be

examined through audience�s frequency of watching art performances/ Uhus- frequency

becomes the dependant variable in this study.

FiFigure 2 Research framework

According to Kotler and Scheff (1997), there are five factors that contribute to

consumer�s decision making process )table 3*/ Lotler ' Brmstrong )3126* refers macro-

environmental force as societal influences that affect organizations in their effort to serve

the customers, which includes demographic, economic, natural, technological, political, and

cultural forces. Cultural factors refer not only to nationality, but also the set of values,

perceptions, perceptions, and behaviors people grew up with (Kotler & Scheff, 1997).

Seference groups- which is defined as any person or group of people who influences people�s

behavior, is the most significant influence (Blackwell, Miniard, & Engel, 2006). Moreover,

psychological factors include people�s attitude and motivation that drives people�s behavior

)Lotler ' Tcheff- 2;;8*/ Mastly- personal factors- which refers to people�s circumstances-

consist of occupation, lifestyle, life-cycle stages, and economic circumstances.

In this study, three factors, namely personal, psychological, and social factors, are

examined closely in relation to audiences� watching behaviors/ Qersonal factors are analyzed

by assessing customer�s demographic background/ Mastly- social factors are assessed by

examining audiences� preferences/ Notivation theory by Norris Iargreaves NcJntyre



(2007) is used to analyze underlying reason that drive the audience to watch art

performances.

Table 2: Factors Influencing Consumer Behavior, adapted from Kotler & Scheff (1997)

Factors Influencing ConsumerBehavior

Forms

Macro-environmental Trends Social, political, economic, and technological forcesCultural Factors Nationality, subcultures, social classSocial Factors Reference groups, opinion leaders, innovativenessPsychological Factors Personality, beliefs and attitude, motivationPersonal Factors Occupation, economic circumstances, family, life-cycle stage

Motivation

Jn addition to understanding people�s underlying traits- it is also important to understand

motivation, or reasons behind people�s action or behaviour/ One of the most popular

motivation is Naslow�s hierarchy of human needs- which categorizes people�s motivation

into five attributes, which are physiological, safety, social, self-esteem, and self-actualization

(Maslow, 1943). In relation to art performance, Morris Hargreaves McIntyre (2007), adapted

Naslow�s theory and identified four key drivers of attendance- social- intellectual- emotional-

and spiritual (table 2). These four components are then broken down into realistic purposes

people have when watching an art performance, as depicted in table 3.

Table 3. Needs, motivations, and drivers matrix, adapted from Morris Hargreaves McIntyre(2007).

Wisitor�s Oeeds ' Notives Drivers & Type ofEngagement

Naslow�s Iierarchy ofHuman Needs

Escapism Stimulate creativityAesthetic pleasureAwe and wonder

SpiritualSelf-actualization

Cognitive / esteem

Love / belonging

Safety

Physiological

Being movedPersonal relevanceNostalgiaSense of cultural identity

Emotional

Academic interestHobby interestSelf-improvement

Intellectual

Social interactionEntertainmentSeeing & doingInclusion & welcomeAccess, comfort, warmth & welcome

Social

RESEARCH METHOD

The method used in this paper is mono-method quantitative analysis. A quantitative data is

collected using online questionnaire to random determine the audiences� values and

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preferences in general. Since it is an online questionnaire, the data were collected at various

times of the day on different days of the week during the first two weeks of July 2016.

Potential respondents were pre-qualified by a preliminary question asking whether they have

watched at least one local art performance in the past two years; those who have are deemed

valid respondents, while who have not are invalid. Due to time limitation of the study, the

data sampling method was not purely random= half of the participants are within the author�s

circle of friends, and the other half are picked by random through social media search.

The sample size of study is 292- which was calculated using Memeshow�s formula

(Lemeshow, Hosmer, Klar, & Lwanga, 1990) for unknown population (equation 1). This

method is used as the data needed to make an assumption regarding the real population of

the study, for instance, the number of performance art audience in a year or proportion of

the population who like watching performance art- is not available/ Uhus- Memeshow�s

formula, which makes use of the validity of the data gathered from the pilot study, suits this

research best (table 4).

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Table 4: Pilot study data

Total Number ofRespondents

Valid Data Percentage

66 52 78,8%

Where n is the sample size, Z is the Z score of the confidence interval, and p is the

expected proportion, and d is the margin of error in estimating p. The confidence level in

this study is set to be 90%. Applying the data in table 4 results in the sample size of 181

(rounded from 180,823), as depicted in equation 2.

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Equation 2: Sample size calculation

This study gathered a total of 206 respondents. Of all responses, sixteen have

inconsistent responses and thus are omitted. Therefore, there are 190 valid respondents that

are categorized in four clusters. Furthermore, the data is examined using two-step cluster

analysis to determine the number and the characteristic of the group.

The survey comprised of 23 questions related to the basic demography of the

audiences, their motivations, preferences, and watching behaviors (see appendix A). Among

these were questions that asked their frequency of watching local art performances, their

favorite activities to do, and their preferred information source.

Furthermore, prior to conducting cluster analysis, an analysis of variance (ANOVA)

is done to determine which variables are significant for the cluster analysis. The significance


International Conference on Ethics of Business, Economics, and Social Science |||| 305

level of the test (alpha) is set to be 0.1, and thus the critical value for the F-test is 1.645.

Therefore, variables which have F-test score of more than 1.645 are significant variables,

while those score below are insignificant (see Appendix B). Furthermore, as some variables

belong to a certain category, the significance of the category is determined using the majority

of the variables significance.

The ANOVA shows that basic demographic profile, such as age, education, jobs,

monthly expenditure, gender, marital status, and domicile, does contributes to the clusters

forming. Besides demographic profiles, the type of show watched, willingness to pay,

motivation, influencing factors, contributing factors, when buying tickets, post-watching

activities, and information also contribute significantly to cluster forming. On the other hand,

the factors that are not significant for the clustering process are preferred activities, interests,

preferred issues, art organizations, and ticket purchase. As a result, the two-step cluster

analysis performed in this study only use variables that are significant.

RESULTS

Analysis of the data revealed many interesting characteristics, attitudes, and behaviors of

local performance art audiences in Indonesia. A strong majority of the respondents (88%)

are in the age range of 18-22 years old, who are usually university students. More than three

quarter (77%) have monthly expenditure of Rp 1.000.000 � Rp 5.000.000. 53% of the

respondents live in Jakarta and 39% in Bandung; the rest live in other Java area and outside

Java. In regards to the types of show, 129 participants indicate that they have watched

theatrical performance, while 119 and 62 have watched music performances and dance

performances, respectively.

The two-step clustering method generates the optimal number of clusters in this

study, which is six clusters. The cluster distribution is shown in figure 3 below.

Figure 3: Cluster distribution for local performance art audience in Indonesia

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CLUSTER DISTRIBUTION

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Cluster 1: Art Enthusiasts

Art enthusiasts, which are the members of cluster 1, are those who actually like and show

highest preference towards watching theatre and music, compared to other groups.

Consequently, art enthusiasts are frequent watchers; 70% of them indicates that they watch

art performances 1-2 times in 3 months.

In terms of motivation, art enthusiasts show all types of motivation. However,

compared to the other clusters, they show more spiritual motivation.

Art enthusiasts prefer to get information from social media and website. Furthermore,

they are least likely to watch art shows at universities; rather, they usually watch art shows

at art venues, such as Ciputra Artpreneur in Jakarta and Teater Budaya Jawa Barat in

Bandung. Lastly, after watching a show, they tend to take photo, talk about it with their

friends who watch together with them, and share their experience to social media.

Cluster 2: Passive Watchers

Cluster 2 is the largest group in this study, with 26% of the respondents categorized as its

member/ Uhe member of cluster 3- which is coined by the term �passive watchers� are those

who do not share their experience to other people besides those whom they watch together

with. All of passive watchers are university students, who rarely watch art performances.

In terms of influencing factors, members of cluster 2 show no significant factors that

influence them to watch art performances. However, they tend to be more influenced by the

location compared to the overall responses. This indicates that they prefer to watch art shows

that is near to them. Lastly, they usually watch art performances to fulfill their intellectual

and spiritual needs.

Cluster 3: Active watchers

Uhe members of cluster 4- known as �active watchers� are mostly students );6-3&*/ Uhey

watch art performances moderately, which is about 1-2 times in 6 months. In contrast to

passive watchers, active watchers tend to share their experiences to wider network. After

watching a show, they not only take photo and talk to their friends, but they also share their

experience on social media and write review. Almost three-quarter share their experiences

on social media and one-third write a review about the show; both of this proportion are the

highest compared to other groups.

In terms of influencing factors, they are most influenced by artists and genre. In fact,

among other groups, active watchers are the ones most influenced by artists, compared to

other clusters. On the other hand, they are least influenced by promotions and directors. In

relation to information source, they prefer to be informed via social media and poster. Lastly,

they are motivated by intellectual, spiritual, and emotion.

Cluster 4: Socializers

Bmong other groups- the members of cluster 5- who is labelled as �socializers�- watch art

performances the least; majority of them only watch art performances less than once in a



year. This group is dominated by employees. In watching art performances, socializers tend

to be driven by social and intellectual needs. Consequently, they are not likely to watch art

performances alone and they are influenced by recommendations from public figures.

Social factor is also apparent in their influencing factors, which are friends and

artists. In fact, they are most influenced by friends, compared to other groups. They are,

however, least influenced by director and promotion. Furthermore, although they show

higher willingness to pay for the ticket, which are around Rp 100.000 � Rp 250.000, they

are most sensitive to price compared to other groups. This suggests that they might take price

into consideration more compared to other groups, when it comes to buying show tickets.

Lastly, similar to cluster 1, they prefer to get informed by social media and website.

Cluster 5: Occasional watchers

Cluster 5 has rather similar profile to cluster 2. Majority of the members, labelled as

�occasional watchers� are university students, who only watch art performances

occasionally. Most of occasional watchers live in Bandung. Their willingness to pay for

show ticket is average, which is around Rp 50.000 � Rp 100.000. Moreover, both passive

and occasional watchers are motivated by intellectual and spiritual needs. They also share

similar preference for information source, which are social media and poster.

Although they seem similar to passive watchers, they differ in terms of influencing

factors. Occasional watchers are most influenced by artists and genre and are least influenced

by directors. Furthermore, although occasional watchers are not motivated by social needs,

they show preference towards watching art performances with friends or relatives. In fact,

they are least willing to watch art shows alone, compared to other clusters.

Cluster 6: Conventional watchers

Cluster 6 is the smallest group, comprising only 8% of the total respondents. Three-quarter

of conventional watchers, who are the members of cluster 6, are students who rarely watch

art performances. They show relatively balanced willingness to pay for the ticket price,

ranging from below Rp 50.000 to Rp 500.000.

Conventional watchers have relatively different preferences compared to other

groups. For example, while four other clusters indicate less preferences for location or

promotion, conventional watchers, on the other hand, are most influenced by these factors.

Moreover, while other clusters are likely to be influenced by artists and genre, conventional

watchers are least influenced by these factors. Another difference is also apparent in the

preferred information source. Although other clusters indicate social media as their preferred

information source, this group actually prefer call center and television advertisement.

In regards to motivation, they usually watch art performances to satisfy their intellectual and

emotional needs. Lastly, they show higher preference towards watching live dance

performance, compared to other groups.

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Table 5: Clusters Summary

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6Percentage 12,6% 26,3% 22,1% 9,5% 21,1% 8,4%Jobcomposition

Balancedbetweenuniversitystudentsandemployees

Alluniversitystudents

Mostlyuniversitystudent

Mostlyemployees

Mostlyuniversitystudents

Mostlyuniversitystudents

Frequency Frequent Notfrequent

Moderate Notfrequent

Notfrequent

No preference

Willingnessto pay

Moderate Moderate Moderate High Moderate No preference

Influencingfactors

Artists &genre

Location Artists &genre

Friends,artists,price

Artists &genre

Location &promotion

Willingnessto watchalone

Yes No Yes No No Neutral

Influencedbypromotion

No Yes Neutral Yes Neutral Neutral

Influencedby publicfigure

No Neutral No Yes Neutral Neutral

Motivation Spiritual Intellectual& spiritual

Intellectual,spiritual,emotional

Social &intellectual

Intellectual& spiritual

Intellectual &emotional

Informationsource

Socialmedia &website

Socialmedia &poster

Socialmedia &poster

Socialmedia &website

Socialmedia &poster

Call center &TVadvertisement

Post-watchingactivities

Moderatelyactive(takephoto, talkwithfriends,share onsocialmedia)

Passive(talk tofriends)

Active(takephoto, talkto friends,shareexperienceon socialmedia,writereview)

Passive(takephoto, talkwithfriends)

Passive(takephoto, talkwithfriends)

Moderatelyactive (takephoto, talkwith friends,share onsocial media)

Effective Segmentation Analysis

Kotler (1997) proposed a tool to analyze the effectiveness of market segmentation, which

consists of five elements known as MASDA: measurable, accessible, substantial,

differentiable, and actionable. Measurable refers to the assessment of the segment size,

which is calculated using measurement tools by Saleeth (2010), by computing the number

of potential customers, volume of purchase, and frequency of purchase. The estimated

market value of the clusters in this study is shown in table 6.



Table 6: Estimated market value of the six clusters (see appendix C)

ClustersPer 1000people

Weightedwillingness to pay

Weightedfrequency

Estimated MarketValue (Rp)

1 126 95833.33 5.71 68,928,125.00

2 263 113000.00 2.10 62,409,900.00

3 220 141666.67 3.64 113,535,714.29

4 94 175000.00 1.97 32,443,055.56

5 209 93125.00 1.53 29,681,265.63

6 84 157812.50 3.03 40,183,007.81

Moreover, accessibility refers to the whether reaching and serving the market can be

done effectively. In terms of the art performances, art organizations could reach the

customers through marketing communication channels they prefer. According to Statista

(2014), the most effective marketing channels according to global marketers is website

marketing and social media; TV advertising and direct marketing are moderately effective,

while print media and radio advertising are the least effective ones. Considering their

preference in terms of information source, audience in cluster 1 and 4 would be the most

accessible. Meanwhile, cluster 2, 3, and 5 would be fairly accessible, and cluster 6 would be

the least accessible.

Substantial concerns about whether the segments are large and profitable enough to

serve. Cluster 2, 3, and 5 comprise large number of people, which is substantial for art

marketers. Moreover, although cluster 4 only makes up less than 10% of the total population,

it has the highest willingness to pay, which makes it profitable to serve.

Differentiable, on the other hand, refers to whether the segments are clearly

distinguishable and behave differently from other segments. In the six segments, clusters 2,

3, and 5 have similarities in terms of willingness to pay, influencing factors, motivation, and

preferred information source. Thus, these clusters are not highly distinguishable. On the

other hand, clusters 1 and 4 respond differently compared to the other clusters, in terms of

influencing factors, frequency, willingness to pay, and motivation. Therefore, these clusters

are easily differentiable. Lastly, cluster 6 shows no preference on some factors, but has

distinct preferences in terms of influencing factors and information source. Thus, cluster 6

is partly differentiable from other clusters.

Lastly, actionable refers to whether effective programs can be designed to attract and

serve the segments. This depends on the strategies used by the art marketers; however, art

marketers could attract these segments with appropriate strategies, which will be described

in the next sub-section. Therefore, all clusters have equal opportunities to be actionable,

depending on the strategies chosen by the art marketers.

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Table 7: Effective Segmentation Analysis

Cluster Measurable Accessible Substantial Differentiable ActionableTargetmarketpriority

1 High Yes No Yes Yes Moderate2 High Moderate Yes No Yes High3 Highest Moderate Yes No Yes Highest4 Low Yes Yes Yes Yes Moderate5 Lowest Moderate Yes No Yes Low6 Low No No Partly Yes Lowest

DISCUSSION

Segmentation study is aimed to provide deeper understanding towards the customers and to

create strategies that suit them best. In regards to the six clusters in local performance art

audiences, art marketers could make use of their distinct preferences and behaviors. The

following recommendations are sorted according to the target market priority.

Cluster 3: Active watchers

Although this group only watch art performance moderately, they could contribute to the art

organizations significantly, as they are relatively a large group. Moreover, tend to share their

experience to wider audiences. Their tendency to post on social media and write a review

after they watch a performance could reach more audiences, and thus, market the show

effortlessly. In order to attract this group, art marketer could tap on their motivation, by

branding the show in a more intellectually intriguing way, for instance by emphasizing that

watching an art performance could increase their creativity. Art marketers could also put

more emphasis on spiritual and emotional needs.

Cluster 2: Passive Watchers

Passive watchers are substantial group, as they are the biggest group of the population.

Therefore, using strategies that appropriate for them could increase their frequency of

watching art performances, and thus could boost the industry significantly.

Art marketers could create interesting promotion to attract passive watchers, as they

are most influenced by promotion compared to other groups. For example, creating a

promotion using referral system, which allows them to get a special price when they tell their

friends about this show, might be attractive to them, as they tend to be influenced by friends.

Moreover, art marketers should use media that are preferred by passive watchers, such as

social media and poster. Lastly, art marketers could emphasize on both intellectual and

spiritual side when marketing an art performance to attract this group.

Cluster 1: Art enthusiasts

Art enthusiasts should be relatively easy to target, as they already show high preference and

high frequency of watching live performances. Art marketers could utilize this by



introducing season ticket, which audience could watch more than one performance in a time

period, with special price.

For this group, artists and genre are important, and thus, art marketers could

emphasize such areas to attract this market. Marketing an art performance to this group could

emphasize on both spiritual and intellectual side, for instance, by showing how the audience

can escape from the reality and at the same time be intellectually stimulated by watching a

certain show.

Cluster 4: Socializers

Although socializers watch art performances least frequently, they are still considerably a

profitable group to be targeted at, as they have higher willingness to pay for the show ticket.

As they watch art performances for social purposes, art marketers could emphasis its

promotion on a more social factors/ Gor example- art marketers could create �family show�

branding for the show or introduce price bundling for buying more than one ticket. The

medium for the marketing should also be differentiated from other groups, as they prefer

website to posters.

Cluster 5: Occasional watchers

As occasional watchers are least willing to watch art performance alone, art marketer could

adopt similar strategy used for socializers. For example, special price for buying more than

one ticket could be attractive to occasional watchers. Moreover, occasional watchers take

photos most, compared to other groups, art marketer could utilize this behavior, by providing

photo booth or other promotion related to taking photos.

Cluster 6: Conventional watchers

Although conventional watchers are not efficient to target, it could become a niche market,

as they show more preference in watching dance performances compared to other groups.

Therefore, art organization specializing in dance performances might want to target

specifically conventional watchers. Furthermore, art marketer could tap on conventional

watchers� intellectual and emotional needs/ Mastly- art marketer should pay more attention

in the media used to promote the show, as conventional watchers tend to prefer call center

and television advertisement, over contemporary media, such as social media and website.

Limitation and Future Research

There are several research limitations that should be considered. As mentioned previously,

due to time limitations, the participants of this study are not purely random, which is also

depicted in the homogeneous respondents. A follow up study with more random respondents

or more specific area may well find different dynamics and characteristic of the audience.

Moreover, as this study covers huge geographical area and huge area of performance art

industry, the findings may not reflect specific issues on a certain area. However, on a macro-

level, the findings and discussion of this study could be an indication of the general audience

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profile of local performance art in Indonesia. As such, future study regarding local

performance art audience in Indonesia is needed in order to have better understanding of the

customers.

CONCLUSION

This study aims to serve as a basis of understanding local performance art audience, as

research covering such topic in Indonesia is scarce. This research shows that variables that

contribute to the forming of the clusters are demographic profile, type of show watched,

willingness to pay, motivation, influencing factors, contributing factors, when buying

tickets, post-watching activities, and information source. The optimal number of clusters in

this study is six, which are then labelled as art enthusiasts, passive watchers, active watchers,

socializers, occasional watchers, and conventional watchers. However, active watchers are

the most effective segment to be targeted at, while conventional watchers are the least

effective one.

Although this study generated conclusive result, further study is encouraged to better

understand the audience, especially for smaller scale. This study indicates that local

performance art audiences have different needs and wants in terms of watching an art show.

Understanding the differences could potentially be translated into different marketing

strategies that might be effective to the segments. It is hoped that this study may be of value

to art marketers in Indonesia to market their products better.

ACKNOWLEDGEMENT

The author gratefully acknowledge the guidance and the support of Ira Fachira, Ph.D, as the

author�s thesis supervisor/

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ISSN: 2528-617X


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APPENDIX A: Survey Questions

No. Section Construct Item Measurement Objective1 1: Personal

identityAge + < 13 years old

+ 13-17 years old+ 18-22 years old+ 23-27 years old+ 28-32 years old+ 33-37 years old+ 38-42 years old+ 43-47 years old+ >47 years old

Years old To understandthe agestructure of theaudiences

2 Education + Elementaryschool

+ Junior highschool

+ High school+ Diploma+ Bachelor+ Master+ Doctorate

Education level To understandthe educationstructure of theaudiences

3 Job + Student+ University

student+ Employee+ Self-employed+ Artists /

musicians

Job role To understandthe jobstructure of theaudiences

4 Monthlyexpenditure

+ < Rp 1.000.000+ Rp 1.000.000 �

Rp 2.500.000+ Rp 2.500.001 �

Rp 5.000.000+ Rp 5.000.001 �

Rp 7.500.000+ Rp 7.500.001 �

Rp 10.000.000+ > Rp 10.000.000

Amount ofmoney

To understandtheexpenditurelevel of theaudiences

5 Gender + Female+ Male

Gender To understandthe profile ofthe audiences

6 Marital status + Single+ Married

Marital status To understandthe profile ofthe audiences

7 Domicile + Jabodetabek+ Bandung+ Semarang+ Yogyakarta+ Others

Residentiallocation

To understandthe profile ofthe audiences

8 Type of show + Theatricalperformance

Types of showthat have been

To understandwhat kinds ofshows that

ISSN: 2528-617X


No. Section Construct Item Measurement Objective

+ Musicalperformance

+ Danceperformance

watched by therespondents

have beenwatched by therespondents

9 Willingness topay

+ < Rp 50.000+ Rp 50.000 � Rp

100.000+ Rp 100.000 � Rp

250.000+ Rp 250.000 � Rp

500.000+ > Rp 500.000

Amount ofmoney

To understandhow muchthey arewilling to payto watch liveentertainment

10 2: Value andmotivation

Value andlifestyle(VALS)(StrategicBusinessInsights,2015)

+ Informationseekers and opento newinnovations

+ Preferfunctionality andproducts that arealready tested

+ Success-oriented+ Tend to be

different fromother people andalways ahead innew trend

+ Tend to believeother people�s recommendationand familiarproducts

+ Follow trend+ Prefer outdoor

and hand-onactivities

+ Prefer routine andfamiliar activities,and tend to beloyal to a brand

Statements To understandtheir valuesand lifestyleusing VALSsystem

11 Motivation(MorrisHargreavesMcIntyre,2007)

+ Social purposes+ Entertainment

purposes+ Interest or hobby+ Emotional

purposes+ To inspire or

enhancecreativity

+ To escape thereality for amoment

5-point scaleindicatingagree/disagree

To understandthemotivationsunderlyingtheir decisionsof watching artperformances,based onMaslowmotivationtheory.



No. Section Construct Item Measurement Objective12 3:

Influencingfactors andalternativesin thedecisionmakingprocess

InfluencingFactors

+ Promotors+ Performing artists+ Family or friends+ Ticket price+ Director /

composers /choreographer

+ Event promotion(advertisementand preview)

+ Show genre+ Location

Ranking ofinfluencingfactors

To understandthe influencefactor of theirdecisions ofwatching artperformances.

13 Contributingfactors

+ Whether therespondents wantto watch aperformance artalone

+ Whether therespondent isinfluenced byother publicfigure who watcha certain artperfomance

+ Whetherpromotionsinfluence them

5-point scaleindicatingagree/disagree

To understandfurther abouttheirinfluencingfactors inwatchingperformanceart

14 Preferredactivities

+ Watching livemusic

+ Watching theatreproduction

+ Watching danceproduction

+ Watching movies+ Listening to

music frompodcast / radio

+ Watchingtelevision

+ Going on avacation

+ Playing games+ Shopping+ Doing sport+ Reading books+ Hangout with

family andfriends

+ Attending events,festivals, orbazaars

Ranking of theactivities thatare preferred bythe respondents

To understandtheirentertainmentalternatives, inorder toevaluate theneedrecognitionstage in thedecisionmakingprocess.

ISSN: 2528-617X


No. Section Construct Item Measurement Objective15 Interests + Books and

literatures+ Music+ Visual arts

(paintings andsculptures)

+ Sport+ Dance+ Theatre+ Fashion+ Design+ Film &

photography+ Computer &

technology+ Games

Ranking ofsubjects thatcapture theinterest of therespondents

To understandtheirentertainmentalternatives, inorder toevaluate theneedrecognitionstage in thedecisionmakingprocess.

16 Preferredissues

+ Social+ Business and

economics+ Politics+ Environment+ Law

Ranking ofissues thatcapture theinterest of therespondents

To understandtherespondents� level ofinterest ofcurrent issues

17 When buyingtickets

+ Early bird / Pre-sale

+ A couple of daysbefore the show

+ On the day of theshow

Timing ofbuyingperformance arttickets

To understandthecircumstancewhichinfluencesthem to buyperformanceart ticket

18 Post-watchingactivities

+ Taking pictures+ Talking about the

show to others+ Share the

experience toothers

+ Writing a reviewabout the show

What activitiesthey are likelyto engage inafter theperformance.

To understandthe activitiesdone on thepost-purchaseevaluationstage in thedecisionmakingprocess.

19 Artorganizations

+ Localperformance artTheatre

+ Gedung KesenianJakarta

+ Taman IsmailMarzuki

+ CiputraArtpreneur

+ Taman BudayaJawa Barat

+ Universities

Places showinglocalperformance art

To find outLocalperformanceartcompetitors, inorder toanalyseevaluation ofalternativesstage.



No. Section Construct Item Measurement Objective

+ Others20 Information

source+ Social media+ Printed ads+ Preview in

magazine orblogs

+ Radioadvertisement

+ Website+ Email+ Hotline / call

center

Ranking ofmarketingcommunicationchannels thatthey prefer

To understandwhich channelfits thecustomers

21 Ticketpurchase

+ Website+ Email+ SMS+ On the spot+ Ticket box

Sales channelthat is preferredby therespondents

To understandwhich saleschannel is themost used,whichindicates itseffectivity

22 Frequency + More than once amonth

+ 1-2 times in threemonths

+ 1-2 times in sixmonths

+ 1-2 times in ayear

+ Less than once ina year

Times per year To find outwhether therespondentsare mostlyfirst-timer orrepeatcustomers

ISSN: 2528-617X


APPENDIX B: ANOVA Table

Model

Sum of

Squares

Mean

Square F Sig. Notes

1 Regression (AGE) 18.824 18.824 15.623 .000b Significant

Residual 225.314 1.205

Total 244.138

2 Regression (EDUCATION) 20.437 10.219 8.496 .000c Significant

Residual 223.700 1.203

Total 244.138

3 Regression (JOB) 23.756 7.919 6.647 .000d Significant

Residual 220.382 1.191

Total 244.138

4 Regression (MONTHLY

EXPENDITURE)

24.700 6.175 5.178 .001e

Significant

Residual 219.438 1.193

Total 244.138

5 Regression (GENDER) 24.714 4.943 4.122 .001f Significant

Residual 219.423 1.199

Total 244.138

6 Regression (MARITAL STATUS) 30.311 5.052 4.300 .000g Significant

Residual 213.827 1.175

Total 244.138

7 Regression (DOMICILE) 30.708 4.387 3.720 .001h Significant

Residual 213.429 1.179

Total 244.138

8 Subset

Tests

(TYPE OF SHOW) 26.548 8.849 8.429 .000i Significant

Regression 57.256 5.726 5.453 .000j

Residual 186.881 1.050

Total 244.138

9 Regression (WILLINGNESS TO PAY) 69.757 3.671 3.558 .000l Significant

Residual 174.381 1.032

Total 244.138

10 Subset

Tests

(VALS) 11.780 1.473 1.430 .187i Insignificant

Regression 69.036 3.835 3.724 .000k

Residual 175.101 1.030

Total 244.138

11 Subset

Tests

(MOTIVATION) 12.134 3.034 3.460 .010i Significant

Regression 109.098 3.209 3.659 .000o



Model

Sum of

Squares

Mean

Square F Sig. Notes

Residual 135.039 .877

Total 244.138

12 Subset

Tests

(INFLUENCING

FACTORS)

12.809 1.830 1.835 .084i Significant

Regression 82.566 3.176 3.184 .000m

Residual 161.572 .997

Total 244.138

13 Subset

Tests

(CONTRIBUTING

FACTORS)

14.398 3.600 3.864 .005i Significant

Regression 96.964 3.232 3.470 .000n

Residual 147.174 .931

Total 244.138

14 Subset

Tests

(PREFERRED

ACTIVITIES)

11.558 .889 1.015 .440i Insignificant

Regression 120.656 2.567 2.931 .000p

Residual 123.482 .876

Total 244.138

15 Subset

Tests

(INTERESTS) 9.636 .964 1.109 .360i Insignificant

Regression 130.292 2.286 2.630 .000q

Residual 113.846 .869

Total 244.138

16 Subset

Tests

(PREFERRED ISSUES) 4.597 1.149 1.336 .260i Insignificant

Regression 134.889 2.211 2.571 .000r

Residual 109.249 .860

Total 244.138

17 Regression (WHEN BUYING

TICKETS)

135.981 2.193 2.555 .000s

Significant

Residual 108.157 .858

Total 244.138

18 Subset

Tests

(POST-WATCHING

ACTIVITIES)

1.946 1.946 2.290 .133i Significant

Regression 137.927 2.189 2.577 .000t

Residual 106.211 .850

Total 244.138

19 Subset

Tests

(ART ORGANIZATIONS) 4.564 1.141 1.358 .252i Insignificant

Regression 142.492 2.127 2.532 .000u

ISSN: 2528-617X


Model

Sum of

Squares

Mean

Square F Sig. Notes

Residual 101.646 .840

Total 244.138

20 Subset

Tests

(INFORMATION

SOURCE)

19.209 2.134 2.900 .004i Significant

Regression 161.700 2.128 2.891 .000v

Residual 82.437 .736

Total 244.138

21 Subset

Tests

(TICKET PURCHASE) 1.084 .271 .345 .847i Insignificant

Regression 166.280 1.868 2.376 .000x

Residual 77.858 .786

Total 244.138



APPENDIX C: Cluster Size Measurement

Clusters 1 2 3 4 5 6

Number of potentialcustomer (per 1000

people)126 263 220 94 209 84

Volumeof

purchase:Proportion

of theclustersthat is

willing topay x

amount ofmoney forart show

ticket

50000 0.00 0.20 0.19 0.00 0.30 0.19

75000 0.88 0.58 0.52 0.00 0.53 0.31

175000 0.08 0.14 0.07 1.00 0.15 0.31

375000 0.04 0.04 0.21 0.00 0.00 0.19

500000 0.00 0.04 0.00 0.00 0.03 0.00

Weightedwillingness to pay

95833.33 113000.00 141666.67 175000.00 93125.00 157812.50

Frequencyof

purchase:Proportion

of thecluster

thatwatches

art showsn timesper year

12 0.08 0.00 0.10 0.00 0.00 0.00

6 0.71 0.14 0.10 0.11 0.03 0.31

3 0.13 0.10 0.50 0.17 0.03 0.13

1.5 0.00 0.40 0.24 0.17 0.70 0.44

1 0.08 0.36 0.07 0.56 0.25 0.13

Weighted frequency 5.71 2.10 3.64 1.97 1.53 3.03

Market Value 68,928,125 62,409,900 113,535,714 32,443,055 29,681,265 40,183,007

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